Optimization and Performance Analysis of Intelligent Video AI Dynamic

In today’s information age,video data,as an important carrier of information,is growing explosively in terms of production volume.The quick and accurate extraction of useful information from massive video data has become a focus of research in the field of computer vision.AI dynamic recognition technology has become one of the key technologies to address this issue due to its powerful data processing capabilities and intelligent recognition functions.Based on this,this paper first elaborates on the development of intelligent video AI dynamic recognition technology,then proposes several optimization strategies for intelligent video AI dynamic recognition technology,and finally analyzes the performance of intelligent video AI dynamic recognition technology for reference.

Optimization of Extraction Technology for Rice Bran Oil

[ Objective ] This study aimed to optimize the extraction technology for rice bran oil. [ Method ] Using rice bran as raw material, effects of ultrasonicassisted extraction technology and different organic solvents, extraction durations, solid-liquid ratios and extraction temperatures on extraction results of rice bran oil were investigated. Based on the results of single-factor experiment, L9 （34 ） orthngonal experiment with three factors at three levels was conducted to optimize the extraction technological parameters, thus obtaining the optimal technological conditions for extracting rice bran oil. [ Result] Anhydrous ethanol led to the best extraction result; after ultrasonic treatment, the extraction rate of rice bran oil from raw material was not enhanced. The optimized technological parameters were ： extraction temperature of 80 ℃, extraction duration of 20 rain and solid-liquid ratio of 1：24 （ g： ml）. Under the optimized technological conditions, the extraction rate of rice bran oil reached 19.33%. [ Conclusion] This study laid solid foundation for further investigation and development of rice bran oil.

Evaluation of Yarn Quality and Optimization of Cotton Spinning Parameter Based on Factors Analysis

In this paper, the spinning parameters are optimized by using the method of factor analysis. The yarns obtained from four different spinning parameters are evaluated by this method. Two common factors, fineness unevenness and tenacity level, are extracted from the seven yarn-quality indexes. The accumulative contribution percentage of the two factors is up to 91.813%,and much information in the yarn-quality indexes is reflected by the two factors. Then the score of each factor is calculated to evaluate the quality of yarn. Based on that, the techniques are optimized. The result is well in line with spinning practices, so it is testified feasibly to use this method to optimize spinning parameter.

Probability Simulation Optimization Approach Using Orthogonal Genetic Algorithm

In order to solve the complex optimization problem dealing with uncertain phenomenon effectively, this paper presents a probability simulation optimization approach using orthogonal genetic algorithm. This approach synthesizes the computer simulation technology, orthogonal genetic algorithm and statistical test method faultlessly, which can solve complex optimization problem effectively. In this paper, the author gives the correlative conception of probability simulation optimization and describes the probability simulation optimization approach using orthogonal genetic algorithm in detail. Theoretically speaking, it has a strong rationality and maneuverability that can apply probability method in solving the complex optimization problems with uncertain phenomenon. In demonstration, the optimization performance of this method is better than other traditional methods. Simulation resuh suggests that the approach referred to this paper is feasible, correct and valid.

The Study on Wheat Concurrent-flow Drying Technology

The relation between technology parameters and performance index of the wheat three-stage concurrent-flow drying technology is studied by use of quadratic orthogonial rotate combinative experiment design method.The optimum parameters of drying technology are obtained by nonlinear optimize corresponding regression model and test.All experiment was finished in concurrent-flow grain drying experiment table.The results of this study will be significant for designing energy-saving grain drying machine.

Applications of smart proxies for subsurface modeling

Using artificial intelligence(AI) and machine learning(ML) techniques, we developed and validated the smart proxy models for history matching of reservoir simulation, sensitivity analysis, and uncertainty assessment by artificial neural network(ANN). The smart proxy models were applied on two cases, the first case study investigated the application of a proxy model for calibrating a reservoir simulation model based on historical data and predicting well production while the second case study investigated the application of an ANN-based proxy model for fast-track modeling of CO2 enhanced oil recovery, aiming at the prediction of the reservoir pressure and phase saturation distribution at injection stage and post-injection stage. The prediction effects for both cases are promising. While a single run of basic numerical simulation model takes hours to days, the smart proxy model runs in a matter of seconds, saving 98.9% of calculating time. The results of these case studies demonstrate the advantage of the proposed workflow for addressing the high run-time, computational time and computational cost of numerical simulation models. In addition, these proxy models predict the outputs of reservoir simulation models with high accuracy.

Lightweight Body-In-White Design Driven by Optimization Technology

Structural optimization technologies are increasingly applied to lightweight automotive structural design.In a body-inwhite(BIW)development project,optimization technologies are applied in three steps that are seamlessly integrated into engineering practice.By following a design-driven approach,an innovative design that was 50.65 kg lighter than the base design was achieved.First,topology optimization was used to investigate the optimal material distribution in a given design space,and helped in extracting the main load path,while considering crashworthiness,NVH,and static stiffness performance requirements.In the second step,the effective design of a beam cross-section and feasible joints was carried out based on optimization technology and expert knowledge.In this step,the deep involvement of manufacturing process experts on stamping and joint connection feasibility analysis increased the chance of success remarkably.The sensitivity analysis,topography optimization,and gauge optimization of the created draft 3D BIW frame comprised the last step before finalizing the initial design.The new design was validated by full load case simulations,including full vehicle crashworthiness analysis,mode frequency,and body mount point dynamic stiffness analysis,and BIW stiffness and component attachment stiffness analysis.The validation results indicate that the new BIW design achieves the performance goal,while being 13.3%lighter than the base design.

Fault self-repair strategy based on evolvable hardware and reparation balance technology

In the face of harsh natural environment applications such as earth-orbiting and deep space satellites, underwater sea vehicles, strong electromagnetic interference and temperature stress,the circuits faults appear easily. Circuit faults will inevitably lead to serious losses of availability or impeded mission success without self-repair over the mission duration. Traditional fault-repair methods based on redundant fault-tolerant technique are straightforward to implement, yet their area, power and weight cost can be excessive. Moreover they utilize all plug-in or component level circuits to realize redundant backup, such that their applicability is limited. Hence, a novel selfrepair technology based on evolvable hardware（EHW） and reparation balance technology（RBT） is proposed. Its cost is low, and fault self-repair of various circuits and devices can be realized through dynamic configuration. Making full use of the fault signals, correcting circuit can be found through EHW technique to realize the balance and compensation of the fault output-signals. In this paper, the self-repair model was analyzed which based on EHW and RBT technique, the specific self-repair strategy was studied, the corresponding self-repair circuit fault system was designed, and the typical faults were simulated and analyzed which combined with the actual electronic devices. Simulation results demonstrated that the proposed fault self-repair strategy was feasible. Compared to traditional techniques, fault self-repair based on EHW consumes fewer hardware resources, and the scope of fault self-repair was expanded significantly.

Using a novel cellular platform to optimize CRISPR/CAS9 technology for the gene therapy of AIDS

Dear Editor,Despite tremendous effort devoted to the development of antiretroviral therapies to combat HIV over the past decades, AIDS remains one of the most important global infectious diseases. According to UNAIDS report on the global AIDS epidemic in 2016, the estimated number of people living with HIV rose from 7.5 million in 2010 to 36.7 million in 2015. Furthermore, drug-resistance HIV strains have recently been reported （Wensing et al., 2017）. Therefore, it is important to develop new therapies to eliminate HIV in the patients. Immortalized cell lines representing the major targets of HIV in human are important for HIV research and therapeutic development.